Data Engineer - Modern Data Platforms

Dariel; Gauteng; On-site; ZAR 600,000 - 900,000; Full time

Job summary

Dariel is seeking a Data Engineer to design, build and support scalable data pipelines within an agile team. You will handle raw data, ensure security and repeatable data flows, and drive insights from large datasets.

The role involves building big data solutions with PySpark and Hadoop technologies, implementing ETL processes, and translating business requirements into robust data architectures for analytics and BI readiness.

Qualifications

• Bachelors degree or equivalent in a relevant field is required.
• AWS Certification is preferred and strongly valued.
• Strong programming or scripting language knowledge across data workloads.
• Ability to model data and understand varied structures for use cases.

Responsibilities

• Architect data analytics framework and scalable pipelines.
• Translate complex requirements into architecture and code.
• Lead batch and real-time analytical solutions with modern tech.
• Develop data feeds from on-premise to AWS Cloud and maintain production feeds.
• Create data marts using ETL tools; manage Databases and operations.

Skills

Programming languages

Data modelling

Distributed systems

Python

PySpark

Spark

Big Data

Education

Bachelor’s Degree in Computer Science, Computer Engineering, or equivalent

AWS Certification

Tools

Talend

AWS EMR

EC2

S3

Job description

Data Engineer

The Data Engineer’s role entails building and supporting data pipelines of which must be scalable, repeatable and secure. This role functions as a core member of an agile team whereby these professionals are responsible for the infrastructure that provides insights from raw data, handling and integrating diverse sources of data seamlessly. They enable solutions, by handling large volumes of data in batch and real-time by leveraging emerging technologies from both the big data and cloud spaces. Additional responsibilities include developing proof of concepts and implements complex big data solutions with a focus on collecting, parsing, managing, analysing and visualising large datasets. They know how to apply technologies to solve the problems of working with large volumes of data in diverse formats to deliver innovative solutions. Data Engineering is a technical job that requires substantial expertise in a broad range of software development and programming fields. These professionals have a knowledge of data analysis, end user requirements and business requirements analysis to develop a clear understanding of the business need and to incorporate these needs into a technical solution. They have a solid understanding of physical database design and the systems development lifecycle.

Responsibilities

• Architects Data analytics framework
• Translates complex functional and technical requirements into detailed architecture, design, and high performing software
• Leads Data and batch/real-time analytical solutions leveraging transformational technologies
• Works on multiple projects as a technical lead driving user story analysis and elaboration, design and development of software applications, testing, and builds automation tools
• Development and Operations
• Database Development and Operations
• Policies, Standards and Procedures
• Business Continuity & Disaster Recovery
• Research and Evaluation
• Creating data feeds from on-premise to AWS Cloud
• Support data feeds in production on break fix basis
• Creating data marts using Talend or similar ETL development tool
• Manipulating data using python
• Processing data using the Hadoop paradigm particularly using EMR, AWS’s distribution of Hadoop
• Develop for Big Data and Business Intelligence including automated testing and deployment

Requisite Experience, Education, Knowledge and/ or Skills

• Bachelor’s Degree in Computer Science, Computer Engineering, or equivalent
• AWS Certification
• Extensive knowledge in different programming or scripting languages
• Expert knowledge of data modelling and understanding of different data structures and their benefits and limitations under particular use cases
• Capability to architect highly scalable distributed systems, using different open source tools
• 5+ years Data engineering or software engineering experience
• 2+ years Big Data experience
• 2+ years’ experience with Extract Transform and Load (ETL) processes
• 2+ years AWS experience
• 5 years demonstrated experience with object-oriented design, coding and testing patterns as well as experience in engineering (commercial or open source) software platforms and large-scale data infrastructures
• Big Data batch and streaming tools
• Talend
• AWS: EMR, EC2, S3
• Python
• PySpark or Spark